• DocumentCode
    3584987
  • Title

    A geometrical a priori for capturing the regularity of images

  • Author

    Gousseau, Yann ; Roueff, Francois

  • Author_Institution
    LTCI, GET, Telecom Paris, Paris, France
  • fYear
    2005
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    We first briefly recall how to model occlusion and scaling in natural images through the use of a stochastic model, the scaling dead leaves model. Then we give a statistical estimator for its scaling parameters, which are related to the regularity of images. Last we show how this model can be used as an a priori for image denoising, in the framework of wavelet coefficients thresholding.
  • Keywords
    image capture; image denoising; statistical analysis; stochastic processes; geometrical a priori; image denoising; image regularity capturing; model occlusion; natural images; scaling dead leave model; scaling parameters; statistical estimator; stochastic model; wavelet coefficient thresholding; Bayes methods; Computational modeling; Estimation; Image denoising; Noise; Noise reduction; Wavelet transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing Conference, 2005 13th European
  • Print_ISBN
    978-160-4238-21-1
  • Type

    conf

  • Filename
    7078285